System and method for identification of transmitters with limited information

ABSTRACT

A system and method are disclosed by which a base transceiver station (BTS) may be uniquely identified. When attempting to determine the location of a mobile unit using signal from multiple BTSs, it is critical that the BTSs be uniquely identified and their position accurately determined. In many cases, the signals received from the BTSs provide limited identification information and cannot be used to uniquely to identify the BTS from which a signal has been received. The present invention uses available information to generate a candidate list and to determine therefrom the most likely candidates for the Measurement BTSs. Based on this information, the system analyzes cell coverage overlap and relative phase delay to determine the likelihood of a candidate BTS being the actual BTS from which a signal is received. As candidate BTSs are uniquely identified, it is possible to use this additional identification information in an iterative process to further identify additional candidate BTSs.

RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.10/014,316, filed Dec. 11, 2001, now U.S. Pat. No. 6,832,090 whichclaims priority to U.S. Provisional Application No. 60/318,661, filed onSep. 10, 2001.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is directed generally to transmitteridentification and, more particularly, to a system and method for theidentification of transmitters using limited information.

2. Description of the Related Art

Existing position location technologies based on global positioningsystem (GPS) use a network of satellites in the sky which transmitsignals at a known time. A GPS receiver on the ground measures the timeof arrival (TOA) of the signals from each satellite it can detect. TheTOA of the signals from the satellites, along with the exact position ofthe satellites and the exact time the signal was transmitted from eachsatellite is used to triangulate the location of the GPS receiver. Atypical GPS receiver requires four satellites to make a triangulation,and the performance of the resulting calculation increases as the numberof satellites that can be detected increases.

In an alternative to, or augmentation of, GPS, an existing network ofcellular base stations can be treated as a network of satellites forpurposes of location determination. Similar to GPS technology, the exactposition of each base station, the exact time at which the base stationis transmitting a signal, and the TOA of the base station signals at amobile unit can be used to triangulate the location of the mobile unit.This technique is described by some service providers as AdvancedForward Link Trilateration (AFLT). Wireless networks may also be used inconjunction with GPS to determine the location of the mobile unit.

A significant problem faced by the mobile station is to measure the TOAof the signals that are received from each base station. Differentwireless technologies may take different approaches to TOA measurements.Code division multiple access (CDMA) is one such technology. CDMAmodulation is one of several techniques that allow a large number ofsystem users to share a communication system. It is possible to utilizemeasurements of conventional CDMA modulation techniques to determine thelocation of a mobile unit using AFLT techniques.

CDMA modulation techniques are disclosed in U.S. Pat. No. 4,901,307,issued on Feb. 13, 1990, entitled “SPREAD SPECTRUM MULTIPLE ACCESSCOMMUNICATION SYSTEM USING SATELLITE OR TERRESTRIAL REPEATERS,” which isassigned to the assignee of the present invention, and the disclosure ofwhich is incorporated herein by reference. The above-referenced patentdiscloses the use of a phase-coherent and chip-synchronous chip sequencethat is defined as a pilot chip sequence, or pilot signal. The pilotsignal can be used to provide phase and time acquisition and tracking,and multi-path correction.

Methods for acquiring the pilot signals are disclosed in theabove-referenced patent and in the following patents: (1) U.S. Pat. No.5,781,543, issued on Jul. 14, 1998 and entitled “POWER-EFFICIENTACQUISITION OF A CDMA PILOT SIGNAL;” and (2) U.S. Pat. No. 5,805,648,issued on Sep. 8, 1998 and entitled “METHOD AND APPARATUS FOR PERFORMINGSEARCH ACQUISITION IN A CDMA COMMUNICATION SYSTEM,” both of which areassigned to the assignee of the present invention and the disclosuresthereof are incorporated herein by reference.

When the mobile unit is first powered on, it must establish acommunication link with a base transceiver station (BTS). The mobileunit will typically receive pilot signals from a plurality of BTSs. Themobile unit will search for the signals from the BTSs and will establisha communication link with a selected BTS to permit the reception andtransmission of data, such as audio signals, over the establishedcommunication link. The selection of a particular BTS and the actualprocess of communication between the mobile unit and the selected BTSare well known in the art and need not be discussed in detail herein.

As discussed in the above-referenced patents, each BTS periodicallybroadcasts the same pseudo-noise (PN) code pilot signal, but with adifferent time offset. That is, each BTS transmits the same PN code, butthe start of transmission of the PN code from the transmitter in eachBTS is delayed in time by a precisely known offset. The time offsets aremeasured in multiples of 64 chips. As those skilled in the art willappreciate, a “chip” is a single piece of data in the PN sequence.Because the data is transmitted at a known rate, chips may be used as ameasure of time. Although the present description may be characterizedin actual units of time, it is more convenient to refer to the time interms of chips or portions of chips because the TOA delays due to the PNoffset as well as propagation delay measurements may be calculated interms of chips.

To acquire the pilot signal, the mobile unit must synchronize with thetime offset and frequency of the signal transmitted by a BTS. The objectof a “searcher” process in the wireless device is to find the timeoffset of the received signal. The searcher uses an estimated frequency.If the estimated frequency is not sufficiently close to the frequency ofthe pilot signal, the received signal will not be acquired.

When a BTS is properly detected, the output of the searcher is a pulse,which may be considered a correlation pulse. This correlation pulse maybe used to measure the TOA of the signal from the BTS. It is necessaryto measure the TOA from a number of BTSs to accurately determine thelocation of the mobile unit. In a typical embodiment, the TOA from atleast four BTSs must be calculated to determine the location of themobile unit. A more accurate determination may be made if TOA signalsare received from additional BTSs.

An accurate determination of the location of the mobile unit requiresprecise identification of each BTS from which a signal is received aswell as the precise time at which signals were transmitted from eachBTS. However, the mobile unit is often unable to precisely identify theBTS because only limited information is received from the BTS. That is,the mobile unit does not always receive complete information from eachBTS that permit the unique identification of each BTS. In a particulargeographic region, multiple BTSs may have the same PN offset resultingin potential ambiguity as to the identification of a BTS from which asignal has been received. Such ambiguity leads to inaccuracies in thelocation determination process. Therefore, it can be appreciated thatthere is a significant need for a technique by which transmitters may beidentified using the limited information received by a mobile unit. Thepresent invention provides this and other advantages as will be apparentfrom the following detailed description and accompanying figures.

BRIEF SUMMARY OF THE INVENTION

In an exemplary embodiment, the inventive method comprises receivingtransmission from a plurality of base stations wherein the transmissionsinclude complete identification data from a first base station and onlypartial identification data insufficient to identify at least a portionof the plurality of base stations. A candidate list is generated toprovide an identification of candidate base stations from whichtransmissions containing only partial identification data may have beenreceived. Candidate base stations are analyzed with respect to basestations that have been uniquely identified and the identity of basestations determined on a basis of the analysis of the candidate basestations. The analysis may include an analysis of areas of coverageoverlap between a known coverage area of the uniquely identified basestation(s) and a coverage area of the selected one of the candidate basestations. Additional analysis of a relative phase delay between one ormore uniquely identified base station and a selected candidate basestation may also be performed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a diagram illustrating the relative position of a mobile unitwith respect to multiple base transceiver stations (BTSs).

FIG. 2 is a functional block diagram of a wireless communication deviceimplementing the system of the present invention.

FIG. 3 is a diagram illustrating the identification of candidate BTSs byanalyzing cell coverage area overlap.

FIG. 4 is a diagram illustrating the identification of candidate BTSs byanalyzing relative phase delays of the candidate BTSs.

FIGS. 5A–5D are diagrams illustrating cell sector coverage of a typicalBTS and coverage modeling by the present invention.

FIG. 6 is a flowchart illustrating the operation of the presentinvention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention uses a data analysis technique to identifytransmitters from which signals are being received. The location of awireless unit is based on a time of arrival (TOA) of the signaltransmitted from a plurality of identified base transceiver stations(BTSs). The delay in the TOA is based on the PN offset as well as thetransmission propagation delay. The TOA offset may be readilydetermined. However, the propagation delay requires the uniqueidentification of each BTS so that the position of each BTS is preciselyknown.

In most cases, the only information available to the mobile unit is thePN offset. As is known in the art, the PN offset is typically inmultiples of 64 chips. However, some service providers use separation ofmore than 64 chips in PN offsets. Given the length of the PN code in thepilot signal, there are only 512 (0–511) possible PN offsets for asystem using 64-chip PN offset separation. As will be described below,this leads to significant ambiguities in uniquely identifying a BTS.

FIG. 1 is a diagram illustrating the operation of a wireless systemusing advanced forward link trilateration (AFLT) to determine thelocation of the mobile unit. As illustrated in FIG. 1, a mobile unit 10is within range of a plurality of BTSs 12–22. To permit normalcommunication, such as voice communication, the mobile unit 10establishes communication links with one or more of the BTSs 12–22,respectively. The information derived in the process of establishing thecommunication links may be used to estimate the TOA and therebydetermine the location of the mobile unit 10 with respect to the BTSs12–22. In FIG. 2, a communication link 24 is established between themobile unit 10 and the BTS 12. It should be noted that it is notnecessary to establish a communication link with a BTS to measure itsTOA. The mobile unit 10 can actually measure the TOA simply by listeningto all the base stations. However, accurate location determinationrequires the identification of each BTS so that the TOA delay based onpropagation delays may be used in the AFLT process. The presentinvention provides a technique for uniquely identifying BTS based on thelimited information available to the mobile unit 10.

In a communication system, signals from a BTS are often propagatedbeyond their normal coverage area by the use of repeaters. A repeaterreceives the signal from the BTS and retransmits the same signal. FIG. 1illustrates a repeater 30 coupled to the BTS 18 via a communication link32. The communication link 32 may be a wireless communication link, afiber optic, hardwire, or other known signal communication link. A BTSwhich has a repeater (e.g., the BTS 18) is known as a donor BTS becauseit “donates” its signal to the repeater. FIG. 1 also illustrates arepeater 34 coupled to the repeater 30 via a communication link 36. Asdiscussed above with respect to the communication link 32, thecommunication link 36 may be a wireless communication link, fiber optic,hardwire, or the like. Use of the repeaters 30 and 34 effectively extendthe range of the BTS 18. A mobile unit, such as the mobile unit 10,which measures a signal from a donor BTS may be receiving that signaldirectly from the BTS or it may be receiving the signal via therepeater. Frequently it is not easily possible for the mobile unit 10 todetermine whether the measured signal has come through the repeater ornot.

The present invention is embodied in a system 100 illustrated in thefunctional block diagram of FIG. 2. The system 100 includes a centralprocessing unit (CPU) 102, which controls operation of the system. Thoseskilled in the art will appreciate that the CPU 102 is intended toencompass any processing device capable of operating thetelecommunication system. This includes microprocessors, embeddedcontrollers, application specific integrated circuits (ASICs), digitalsignal processors (DSPs), state machines, dedicated discrete hardware,and the like. The present invention is not limited by the specifichardware component selected to implement the CPU 102.

The system also preferably includes a memory 104, which may include bothread-only memory (ROM) and random access memory (RAM). The memory 104provides instructions and data to the CPU 102. A portion of the memory104 may also include non-volatile random access memory (NVRAM).

In one embodiment, the location of the mobile unit 10 may be determinedsolely by processing that occurs within the mobile unit itself. In analternative embodiment, the mobile unit will transmit data that itreceives to a BTS (e.g., the BTS 12) to permit the position calculationto be determined by the BTS. In yet another alternative embodiment, themobile unit transmits data to the BTS (e.g., the BTS 12) which in turntransmits the data to a position determining entity (PDE) 26. FIG. 1illustrates the PDE 26 as coupled to the BTS 12 via a communication link28. The communication link 28 may be a landline or another wirelessconnection. In addition, the PDE 26 may be coupled to a large number ofBTSs (e.g., the BTSs 12–22) and may receive data relating to the presentinvention from any one of the BTSs. The advantage of a centrally locatedpositioning determining entity, such as the PDE 26, is that statisticalanalysis, base station lookup, and other processes, which will bedescribed in detail below, may be more efficiently done by a centrallylocated unit rather than processed by the mobile unit 10. It can beappreciated that the quantity of information required regarding thelocation of all BTSs can be more efficiently stored in a centralized PDErather than provide for increased storage requirements for the mobileunit 10. However, the present invention is not limited by the specificlocation at which the position of the mobile unit 10 is determined.

In one embodiment, the system 100 is implemented in a wirelesscommunication device such as a cellular telephone, also includes ahousing 106 that contains a transmitter 108 and a receiver 110 to allowtransmission and reception of data, such as audio communications,between the system 100 and a remote location, such as a BTS (e.g., theBTS 12 of FIG. 1). The transmitter 108 and receiver 110 may be combinedinto a transceiver 112. An antenna 114 is attached to the housing 106and electrically coupled to the transceiver 112. The operation of thetransmitter 108, receiver 110, and antenna 114 is well known in the artand need not be described herein except as it relates specifically tothe present invention.

In an implementation for a CDMA device, the system also includes asearcher 116 to detect and quantify the level of signals received by thereceiver 110. The searcher 116 detects one or more parameters, such as atotal energy, pilot energy per pseudo noise (PN) chip, power spectraldensity, and other parameters, as is known in the art. The searcher 116performs a correlation analysis to determine time of arrival (TOA) froma location, such as the BTS 12 (see FIG. 1).

The searcher 116 performs a correlation analysis between a referencesignal and a received signal and generates a correlation output signal.A number of different measures, such as total energy, pilot energy perPN chip or power spectral density, may be used as the correlation value.One commonly used measure is simply the received signal strength such asmay be indicated by the received signal strength index (RSSI).

A signal analyzer or modeling processor 120 analyzes the correlationsignals and uses a statistical model 122 to uniquely identify the BTSswhose signals are received by the mobile unit 10. As discussed above,the position of the mobile unit may be determined by processing withinthe mobile unit itself or by an external entity, which is illustratedgenerically in FIG. 1 as the PDE 26. The signal analyzer 120 andstatistical model 122 may not be required in the mobile unit 10 if theposition is determined by an external entity, such as the PDE 26. Forposition determination by the PDE 26, the signal analyzer 120 and thestatistical model 122 may be located within the PDE 26 and remote fromthe mobile unit 10, as illustrated by the dashed lines in FIG. 2. Theoperation of the signal analyzer 120 and statistical model 122 aredescribed in greater detail below. The system 100 includes a timer 124to provide system timing that is used to measure delay times in thearrival of signals from different sources (e.g., the BTSs 12–22 and oneor more GPS satellites). The timer 124 may be a stand-alone device orpart of the CPU 102.

The various components of the system 100 are coupled together by a bussystem 126, which may include a power bus, a control signal bus, and astatus signal bus in addition to a data bus. However, for the sake ofclarity, the various buses are illustrated in FIG. 2 as the bus system126.

One skilled in the art will appreciate that the system 100 illustratedin FIG. 2 is a functional block diagram rather than a listing ofspecific components. For example, although the searcher 116 and signalanalyzer 120 are illustrated as two separate blocks within the system100, they may be in fact embodied in one physical component, such as adigital signal processor (DSP). They may also reside as program codes inthe memory 104, such code being operated on by the CPU 102 or aprocessor (not shown) in the PDE 26 (see FIG. 1). The sameconsiderations may apply to other components listed in the system 100 ofFIG. 2, such as the statistical model 122.

Operation of the components shown in the system 100 of FIG. 2 will beexplained in detail. To assist in proper understanding of the presentinvention, a brief description of TOA processing using, by way ofexample, a CDMA mobile unit, will be presented. A mobile unit (e.g., themobile unit 10 in FIG. 1) implementing the system 100 of FIG. 2 isinitially assigned a pseudo noise (PN) code. The PN code may be storedin the memory 104 as a local reference. When a base station (e.g., theBTS 12) transmits data to the mobile unit 10, the base station transmitsthe PN code. The system 100 continuously searches for a correlationbetween the local reference (i.e., the stored PN code) and transmitteddata (i.e., the transmitted PN code).

The PN offsets are selectively assigned to BTS transmitters so that theoffsets in a geographic region are spread out as much as possible toavoid interference between transmitters. The transmitters (e.g., thetransmitters in the BTSs 12–22) may be identified by transmittedidentification data, but are sometimes labeled only by their PN offsettime. For example, the transmitter in BTS 12 may be identified as PN 4to indicate that it transmits the PN code at an offset of 4×64 chips. Inthe present example, the transmitters 14 and 16 may be identified as PN12 (i.e., 12×64 chips) and PN 25 (i.e., 25×64 chips), respectively, toindicate the offset times at which each will transmit the PN code.

It should be understood, however, that regardless of how the BTStransmitters are labeled, the relative offset of each with respect toeach other can be established from the information encoded in thesignals. The receiver 110 (see FIG. 2) in the mobile unit 10 will detectthe PN offset from each of the transmitters in the geographic area(e.g., the transmitters in the BTSs 12–22).

When the PN code is transmitted from a BTS (e.g., the BTS 12) there maybe a delay due to the PN offset assigned to each transmitter. Inaddition, there is a propagation delay that is indicative of thedistance between the transmitter and the mobile unit 10. It is thispropagation delay that can be measured by the system 100 to determinethe location of the mobile unit 10. For example, the correlation pulsefrom the BTS with the lowest PN offset will arrive at the mobile unit 10prior to arrival of signals from any other BTS. The system 100 mustaccurately determine the TOA of this first signal and may arbitrarilyassign it to a time offset of zero. Subsequent correlation pulses fromother BTSs and/or GPS satellites (not shown) will also be detected bythe mobile unit 10, but with additional delays that are the result ofthe PN offset and the propagation delay. The delay associated with thePN offset is precisely known. Thus, a residual delay is propagationdelay as a result of the distance between the BTS and the mobile unit10.

As one skilled in the art can appreciate, propagation delays can only beused to determine MS position if each BTS is uniquely identified.However, most information received from the BTSs simply indicate the PNoffset. Because there are a limited number of possible PN offsets, themobile unit 10 cannot always uniquely identify the particular BTS. Forexample, assume the mobile unit 10 only receives an offset value thatidentifies a particular BTS as PN 25 (i.e., 25×64 chip offset). Theremay be thousands of BTSs within the country that have an identicaloffset. Thus, it is not possible to uniquely identify a particular BTSbased only on this information.

The system 100 utilizes this limited information and generatesadditional information to establish a list of possible candidates andselect the most likely candidates. As will be discussed in greaterdetail below, the system 100 then analyzes the list of likely candidatesusing a variety of techniques to uniquely identify a particular BTS.

The mobile unit 10 does have additional information derived from atleast one BTS. Returning momentarily to FIG. 1, the mobile unit 10initially establishes a communication link with a selected BTS. Aspreviously noted, the process of selecting one BTS with which tocommunicate is known in the art and need not be described herein.However, the primary BTS with which the mobile unit 10 communicates isreferred to in the industry as the “Serving” BTS. In the example of FIG.1, the mobile unit 10 establishes the communication link 24 with the BTS12. In this example, the BTS 12 would be considered the Serving BTS. Inestablishing the communication link 24, the mobile unit 10 receives datathat uniquely identifies the BTS 12.

Under telecommunication standard TIA-801 (Position Determination) andTIA-801-1 (Position Determination) (hereinafter TIA-801), the ServingBTS (e.g., the BTS 12 of FIG. 1) provides a number of parametersincluding NID, SID, BAND_CLASS, CDMA_FREQ, and BASE_ID. As those skilledin the art will recognize, NID refers to network identification, SIDrefers to system identification, BAND_CLASS refers to a set of channelsallocated to that communication system as well as a number scheme forthat communication system, CDMA_FREQ refers to the operational frequencyon which the BTS and MS are communicating, and the BASE_ID identifiesthe particular BTS (e.g., the BTS 12 in FIG. 1) and includes a sectoridentification. This information can uniquely identify the BTS. Withthis information, the precise position (i.e., latitude and longitude) ofthe Serving BTS can be determined.

As those skilled in the art will appreciate, a typical BTS actuallycomprises independent transmitter receiver pairs that control a sector.Each sector is essentially an independent BTS. Thus, the sectoridentification provided under TIA-801 uniquely identifies the ServingBTS (e.g., BTS 12 of FIG. 1) and the particular sector of the ServingBTS with which the communication link 24 has been established.

Another telecommunications industry standard, J-STD-036(E)911 (Phase 2),J-STD-036(E)911 (Phase 2-Addendum 1) (hereinafter J-STD-036), providesinformation regarding the Serving BTS, including Market ID, SwitchNumber, Band Class, CDMA Freq., and Cell ID. The Market ID in thetelecommunication standard J-STD-036 is typically the same as the systemidentification in TIA-801 while the Cell ID in J-STD-036 is typicallythe same as the BASE_ID in TIA-801. Thus, under telecommunicationstandard J-STD-036, the mobile unit 10 receives sufficient informationto uniquely identify the Serving BTS.

Given this minimal information, the system 100 can uniquely identifyother BTSs from which signals are received. For purposes of the presentinvention, the location of the mobile unit 10 is determined by measuringTOA from a “Reference” BTS and three or more “Measurement” BTSs. In mostcases, the Reference BTS will be the same as the Serving BTS unless ahand-off has occurred. However, for the sake of simplicity andunderstanding the present invention, the Serving BTS will be consideredthe same as the Reference BTS. In the example of FIG. 1, theServing/Reference BTS is the BTS 12. The BTSs 14–22 are consideredMeasurement BTSs for purposes of the present invention.

As discussed above, the mobile unit 10 has sufficient data to uniqueidentify the BTS 12. However, signals from the Measurement BTSs (e.g.,the BTSs 14–22) typically only include the PN offset, BAND_CLASS, andCDMA_FREQ (under the telecommunication standard TIA-801).

Prior to the receipt of any information, the set of possible BTSscomprises all BTSs in the country except for the Reference BTS (e.g.,the BTS 12). With the PN data received from the measurement BTSs (e.g.,the BTSs 14–22), the set of possible BTSs is narrowed to those BTSs inthe country that have matching PN offsets and transmit frequencies.However, this is typically an insufficient set of data from which thesystem 100 can uniquely identify the Measurement BTSs.

To further narrow the set of possible BTSs, the system 100 utilizes theposition information regarding the Reference BTS (e.g., the BTS 12 ofFIG. 1). For example, if the Reference BTS 12 is located in Seattle,Wash., it is known that the Measurement BTSs 14–22 must be locatedwithin that geographic region. The system 100 performs statisticalanalysis to determine the amount of overlap in coverage areas betweenknown BTSs and a possible Measurement BTS and may also perform relativephase measurements to uniquely identify each measurement BTS. Thecoverage overlap and relative phase measurement processes are describedin greater detail below.

The system 100 generates a large candidate BTS list of all BTSs thatmatch the detected PN offset numbers, BAND_CLASS, and frequency. Thecandidate list may be stored, by way of example, in the memory 104 (seeFIG. 2) if the positioning determining entity is within the mobile unit10 or within a memory (not shown) in the PDE 26 (see FIG. 1). The system100 can limit the candidate list to BTSs that are located anywhere nearthe known coverage area. The known coverage area is based on theReference BTS. The known coverage area may be further based on anyMeasurement BTS that has been previously identified by the system. Aswill be described in greater detail below, the process performed by thesystem 100 is iterative. That is, when the first Measurement BTS hasbeen uniquely identified, that information may be used to uniquelyidentify subsequent Measurement BTSs. As more and more Measurement BTSsare identified, it provides further information to the system 100 usesthe information from the newly identified Measurement BTS to helpidentify the remaining Measurement BTSs.

Following the generation of a candidate list, the system 100 selects themost likely candidates. In certain cases, the geographic region analysisdescribed above may be sufficient to uniquely identify one or more ofthe candidate BTSs as Measurement BTSs. For example, there may be onlyone candidate BTS having a particular PN offset that is located withinthe state in which the Reference BTS is located. As previouslydiscussed, the unique identification of a Measurement BTS can be used toprovide further data which additional BTSs may be uniquely identified.

In addition, the system 10 select candidates for the Measurement BTSsbased on coverage overlap between the known coverage area and thecoverage area of possible candidates. In the example of FIG. 1, theReference BTS 12 has a known coverage area based on data developed atthe time of installation of the BTS, such as, by way of example,transmitter power, antenna pattern, and terrain/land-use data. Thesystem 100 calculates a statistical measure of possible overlap in thecoverage between the known coverage area and the coverage of a potentialcandidate Measurement BTS.

FIG. 3 provides an example of the operation of the system 100 to analyzecoverage area overlap. In the example illustrated in FIG. 3, a knowncoverage area 150 corresponds to the coverage area of a uniquelyidentify BTS, such as the Reference BTS (e.g., the BTS 12 of FIG. 1).Using iterative process, described above, the system 100 may useinformation from any other uniquely identified Measurement BTS (e.g.,the BTSs 14–22 of FIG. 1). Thus, the known coverage area 150 describedwith respect to FIG. 3 may refer to the coverage area of any uniquelyidentified BTS.

For the sake of convenience, the coverage areas are illustrated in FIG.3 as circular patterns. Those skilled in the art will recognize thatgeographic features and/or manmade structures may alter the actualcoverage area. The use of circular areas of coverage is not unreasonableand leads to a simplification in the mathematical processes. However,the present invention is not limited to analysis of circular areas only.

The system 100 uses statistical techniques to determine the probability(or likelihood) that the mobile unit is detecting signals from aparticular BTS. The system 100 uses the statistical model 122 (see FIG.2) to determine the probability of coverage area overlap between a knownBTS and a candidate BTS and relative phase difference between a knownBTS and a candidate BTS. A normal Gaussian distribution (sometimesreferred to as a bell-shaped curve) is used to illustrate probabilitieswith the center or mean of a probability distribution being the peakpoint in the Gaussian distribution. One standard deviation (sometimesreferred to as one-sigma) from the mean results in approximately a 68%probability that a particular measure falls within the Gaussiandistribution. A range of two standard deviations (sometimes referred toas two-sigma) results in approximately 95% probability of inclusionwithin the distribution.

The system 100 calculates probabilities of the mobile unit 10 beingwithin a particular area of coverage. A one-dimensional probabilisticcalculation is relatively simple to perform using the Gaussiandistribution described above. However, the system 100 must calculateprobabilities in two dimensions to accommodate variations in thelocation of the mobile unit in the North-South direction as well asvariations in the East-West direction. To accommodate suchtwo-dimensional probabilities, the system 100 calculates a horizontalestimated position error (HEPE) based on possible errors in twodirections. In the example in FIG. 3, the HEPE of the known coveragearea 150 is calculated as the square root of the sum of squares oferrors in each of the two dimensions. If one assumes a one-sigma (i.e.,one standard deviation) from the mean in a Gaussian distribution, theHEPE may be represented by the following:

$\begin{matrix}{{HEPE} = \sqrt{\sigma_{N}^{2} + \sigma_{E}^{2}}} & (1)\end{matrix}$where the σ_(N) ² indicates a one-sigma error in the North-Southdirection and σ_(E) ² indicates a one-sigma error in the East-Westdirection. Those skilled in the art will recognize that the HEPErepresents the diagonal of a rectangle surrounding the error ellipse.Because the coverage areas are illustrated as circles, the HEPErepresents the diagonal of a square.

As illustrated in FIG. 3, the known coverage area 150 has an HEPEdistance illustrated as r₁, which is based on a one-sigma deviation fromthe Gaussian mean. Also illustrated in FIG. 3 are three candidate BTSs,each of which has an identical PN offset of 25 (i.e., 25×64 chips). ThePN 25 candidates 1 and 3 in FIG. 3 have respective coverage areas 152and 156 that do not overlap with the known coverage area 150. Incontrast, there is overlap between the known coverage area 150 and acandidate coverage area 154 corresponding to the PN 25 candidate 2. Theone-sigma distance for the PN 25 candidate 2 is illustrated in FIG. 3 bythe value r₂. The distances r₁ and r₂ indicate the relative size ofcoverage area of the known coverage area 150 and the candidate coveragearea 154. The distance from the center of the known coverage area 150and the center of the candidate coverage area 154 is illustrated in FIG.3 by the reference D.

The statistical model 122 (see FIG. 2) of the system 100 calculates ameasure of coverage overlap using the relative size of coverage areasand the distance D separating the centers of coverage areas. Thisoverlap may be represented by the following:

$\begin{matrix}\left. {{Overlap}\mspace{14mu}\left( {{in}\mspace{14mu}{sigmas}} \right)}\rightarrow\frac{D}{\sqrt{r_{1}^{2} + r_{2}^{2}}} \right. & (2)\end{matrix}$where all terms have been previously defined. A normal distributionstatistical evaluation may be made of the term in equation (2) togenerate a probabilistic measure of overlap in the known coverage area150 and the candidate coverage area 154.

The normal distribution density function is sometimes calculated usingthe following:

$\begin{matrix}{{{ND}(x)} = {\frac{1}{2\;\pi}\;{\mathbb{e}}^{\frac{- x^{2}}{2}}}} & (3)\end{matrix}$where x is the number of standard deviations away from a perfect overlapbetween the known coverage area 150 and the candidate coverage area 154.For relative probabilities, this equation may be simplified as thefollowing:

$\begin{matrix}{{{ND}(x)} \cong {\mathbb{e}}^{\frac{- x^{2}}{2}}} & (4)\end{matrix}$where all terms have been previously defined.

As an example of the application of the coverage overlap modelillustrated above, consider that the distances r₁ and r₂ in the exampleof FIG. 3 are 2.0 and 1.0, respectively, while the distance D is 1.1.Note that these distances may be measured in convenient units, such askilometers or miles. Inserting these values into equation (2) provides aresult of 0.49. Substituting that value as x in equation (4) provides aresult of 0.886. This indicates an 88.6% probability of perfect overlapbetween the known coverage area 150 and the candidate coverage are 154.Note that a perfect overlap gives the result of 1.0=100%.

In contrast, the one-sigma size of the coverage area 152 results in avalue r₂ equal to 1.5 while the distance D between the center of thecoverage area 152 and the center of the known coverage 150 is 4.0 units.Applying equation (2) to these values provides a result of 1.6.Substituting that value into equation (4) provides a result of 0.278,which indicates a 27.8% probability of perfect overlap between the knowncoverage area 150 and the candidate coverage 152. Thus, it can be seenthat there is a greater probability (i.e., likelihood) that a candidateBTS identified only as PN 25 would be the PN 25 candidate 2 rather thanthe PN 25 candidate 1.

The system 100 can eliminate candidate BTSs based solely on the coveragearea overlap model. However, those skilled in the art will recognizethat there is some probability, however small, that the BTS could be, byway of example, the PN 25 candidate 1 illustrated in FIG. 3.Accordingly, the system 100 will only eliminate a candidate if theprobabilities calculated using equation (4) differ by a factor of 10 orother value chosen for relative confidence ratio. That is, a candidatewill be eliminated based solely on coverage area overlap only if someother candidate is at least 10 times more likely to be the detected BTS.In the example illustrated above, the PN 25 candidate 2 is slightly morethan three times more likely than the PN 25 candidate 1 to be the BTSdetected by the mobile unit 10. Therefore, the system 100 will performadditional analysis to uniquely identify the candidate BTS.

Although not described herein, the system 100 would perform a similaranalysis with respect to the PN 25 candidate 3. In an exemplaryembodiment, the system 100 will analyze any candidate BTS using equation(4) if the result of equation (2) is less than 8. This first step ofanalysis ensures that even candidates with a very low probability ofcoverage overlap will be analyzed using equation (4). If the amount ofthe one-sigma overlap in equation (2) equals 8, the probability usingequation (4) is approximately 1.26×10⁻¹⁴. As a practical matter, thesystem 100 will eliminate any candidate whose one-sigma overlap has sucha large value. This may typically occur in a situation where greatdistances separate the candidate coverage area from the known coveragearea. For example, if the known coverage area 150 is in Seattle, Wash.and a candidate BTS is in San Francisco, Calif., the distance Dseparating the two BTSs is so large that the probability of receptionfrom the San Francisco BTS can be ignored.

The system 100 would also check that the probability of the most-likecandidate is reasonable. If the probability of the most likely candidateis, by way of example, 0.001, (i.e., 0.1%), this suggests a fairly poorfit of the candidate BTS and other known information, and thepossibility that the correct BTS is not in the original BTS database maybe higher. The system 100 will verify that the fit of the best candidateis at least 0.01 (i.e., 1%) or other value chosen for minimum likelihoodthreshold, to reduce the change of matching a measurement with apotentially incorrect BTS.

In addition to a coverage area overlap analysis described above, thesystem 100 uses a relative phase model to further narrow the list ofcandidate BTSs. The term “relative phase” is used to indicate thedistance from the candidate BTS to the mobile unit 10. As discussedabove, each BTS transmits an identical PN sequence, but with known timedelays or PN offsets. When two candidate BTSs have an identical PNoffset, the signal will be detected by the mobile unit 10 (see FIG. 1)at different times (or phase offsets) based on the distance from thecandidate BTS to the mobile unit. In the example of FIG. 1, the mobileunit 10 is known to be within the coverage region of the Reference BTS12. If two candidate Measurement BTSs are also within that coverageregion, it may be possible to eliminate one of the candidate BTSs basedon the propagation delay, which is indicative of the relative phase. Forexample, if one candidate BTS is within two miles of the Reference BTSwhile the other candidate BTS is twenty miles from the Reference BTS,the relative phase between the two can be used to eliminate one of thecandidate BTSs.

In an exemplary embodiment, the statistical model 122 (see FIG. 2) usesa double-difference relative phase model as follows:ND([(d _(K) −d _(i))−(p _(K) −p _(i))]/S _(C))  (5)where d_(K) is the distance from the center of the combined coveragearea (i.e., the combined coverage area of the candidate BTS and theknown BTS) to an already known BTS, d_(i) is the distance from thecombined coverage area center to the candidate BTS, p_(K) is the phasemeasurement to the known BTS, p_(i) is the phase measurement to thecandidate BTS, and S_(C) is the size of the expected double-differencephase error based on the combined coverage area. The term “doubledifference” refers to a statistical calculation based on two differencemeasurements (i.e., the difference in distance minus the difference inphase).

The phases p_(K) and p_(i) are adjusted for known BTS biases such asforward link hardware delay. As those skilled in the art willappreciate, hardware delays may occur due to processing withincircuitry, filters, connector cables, and the like. Uncertainties in thephase measurements due to BTS bias uncertainty, and possible propagationdelays and measurement errors are combined with the denominator (S_(C))of the relative phase test. Additionally, the relative phase test can beremoved, given far less weight, or made one-sided if either the knownBTS or the candidate BTS has a repeater which can significantly delaythe relative phase measurement. For measurement purposes, the phase of asignal that goes through a repeater (e.g., the repeater 30 of FIG. 1) isdelayed and appears further away than a signal coming from a donor BTS(e.g., the BTS 18). Compared to the normal direct signal, the repeatersignal is delayed by both hardware delay, due to filters, cables, andthe like, and is further delayed because the signal path from the donorBTS may be indirect, resulting in additional delay.

The relative phase test may be modified for the presence of repeaters intwo different ways. In one case, the location and signal delays of allrepeaters are known. In the second case, it is known that a given BTSmay have one or more signal repeaters, but the location and/or signaldelays of these repeaters are not known. In the first case, certain BTSs(e.g., the BTS 18 of FIG. 1) are known to have one or more repeaters(e.g., the repeaters 30 and 34), and the location and signal delays ofeach of the repeaters is known. In this case, each repeater of each BTScan be treated as another candidate BTS. The candidate repeater lookssimilar to the donor BTS except that it is in a different location witha different, usually much higher hardware delay. Further, each candidaterepeater has a different sector center and maximum antenna range. Thecandidate repeater is added to the candidate list in the same way as anormal BTS only subject to the same coverage area and phase tests as anyother candidate. Assuming such repeater information is available, thisis the preferred method of treating a repeater because it increases thelikelihood that both the donor BTS and each repeater can be used as thesignal original of measurement.

In the second case, a BTS, such as the BTS 18 of FIG. 1, may have one ormore repeaters (e.g., the repeaters 30 and 34), but the location andsignal delays of the repeaters is not known. If a signal comes from arepeater, it is delayed longer than a phase delay coming directly fromthe donor BTS. As a result, the relative phase test described aboveneeds to allow for a phase that is equal to, or longer than, a signalthat came directly from the donor BTS. In the case where a candidate BTSmay have a repeater, the relative phase test is modified so that thedouble-difference is consistent with a much longer than expected phasedelay from that candidate BTS. For example, the relative probability isnot scored based on the approximation of Equation (4), but is insteadequal to the maximum value of Equation (4) or 0.5, which ensures that along phase delay never has a score worse than 0.5. This effectivelymakes the phase test one-sided. One skilled in the art will recognizethat other techniques may be used to compensate for long phase delaysthat may be introduced by repeaters. Additionally, when selecting acomparison BTS for relative phase delay test measurements, it may beuseful to avoid a comparison with a BTS with repeaters.

The combined coverage area is a probabilistic measure of the combinedareas of coverage of the known BTS and the candidate BTS. Details on themeasurement of the combined coverage area are provided below. Therelative phase model is used to determine whether the phase delaymeasured by the mobile unit 10 (see FIG. 1) is consistent with thedistances between the known BTS and the candidate BTS. As discussedabove, the known BTS may be the reference BTS (e.g., the BTS 12 ofFIG. 1) or any other measurement BTS that has already been uniquelyidentified.

The example presented above is one technique that may be used todetermine such relative phase differences. Those skilled in the art willrecognize that other techniques may be used to determine such phasedifferences. The present invention is not limited by the specificanalysis described above to determine the relative phase differences.

The calculation of the relative phase is illustrated in FIG. 4 where theapproximate center of a combined coverage area 160 is indicated by thereference numeral 164. The distance d_(K) is the distance between thecenter 164 of the combined coverage area 160 and a known BTS 166. Asdiscussed above, the known BTS 166 may be the Reference BTS, ServingBTS, or a uniquely identified Measurement BTS.

A candidate BTS 168 has a coverage area 162, which is modeled as acircular coverage area. As shown in FIG. 4, the candidate BTS 168 is notlocated at the center of the candidate coverage area 162. This is due tothe fact that a typical BTS is not omni-directional, but is broken upinto a number of sectors. The sector could be modeled by the system 100as a pie-shaped sector. However, such modeling is often inaccurate dueto back scatter from the antenna, as well as reflection off buildings,natural terrain, and other objects. Thus, the candidate coverage area162 may be modeled as a circle. Similarly, the known BTS 166 istypically not located at the center of the known coverage area (notshown in FIG. 4) for the reasons discussed above.

The coverage areas of each BTS (or each cell sector) is determined atthe time of installation and is known. The combined coverage area,indicating the coverage area of the known BTS 166 and the candidate BTS168, can be calculated linearly by calculating an area of overlap ofcircular areas of coverage. Alternatively, the combined coverage areamay be calculated weighting the coverage areas. The determination of thecombined coverage area is described in greater detail below.

The combined coverage area 160 is determined based on coverage areasmapped when a BTS is installed and calibrated. The combined coveragearea 160 is a probabilistic estimation of coverage areas of the knownBTS 166 and the candidate BTS 168. As discussed above, thetwo-dimensional positional error, referred to as HEPE provides a measureof the statistical uncertainty in measuring the combined coverage area160. In the system 100, a distance S_(C) is based on HEPE coverage andrepresents a one-sigma uncertainty in the relative phase.

The distance between the center 164 of the combined coverage area 160 tothe candidate BTS 168 is indicated by d_(i). Phase measurements p_(K)and p_(i) are measured by the mobile unit 10 and provided to the PDE(e.g., the PDE 26 of FIG. 1) through the BTS using telecommunicationstandard TIA-801.

As noted above, the system 100 can calculate the expected relative phasedifference and compare the expected phase difference with actualdistance measurements. The system 100 may apply the normal distributionequation (4) to calculate the probability that the candidate BTS isconsistent with the phase and distance measurements. If multiplecandidate BTSs (with the same PN) are detected by the system 100, it maybe possible to eliminate one or more the candidate BTSs based on therelative phase difference. That is, the candidate BTS must have a phasedifference that is reasonable given the location of the known BTS fromthe center 164 of the combined coverage area 160 to the distance fromthe candidate BTS from the center of the combined coverage area.Candidate BTSs that are inconsistent can be eliminated from thecandidate list.

The relative phase model is applied to other candidate BTSs as well. Forexample, FIG. 3 illustrates three candidates that all have the identicalPN 25 offset. The analysis process described above is applied to each ofthe candidate BTSs (e.g., the PN 25 candidates 1–3 of FIG. 3) with aprobability calculated for each candidate BTS. As noted above, acandidate BTS may be eliminated based solely on the coverage areaoverlap model if the coverage overlap of another BTS is at least 10times more likely than the coverage area overlap of the BTS to beeliminated. Similarly, a particular candidate BTS may be eliminatedbased solely on the relative phase model if the phase differenceprobability of another BTS is at least 10 times more likely than thephase difference probability of the BTS to be eliminated. This processassures that a low probability candidate BTS will be eliminated withlittle likelihood of eliminating the wrong BTS.

The probabilities of the coverage area overlap model and the relativephase model may be combined to eliminate candidate BTSs. In one example,the probability of the coverage area overlap model is multiplied by theprobability of the relative phase model. The combination ofprobabilities serves to further eliminate unlikely BTSs from thecandidate list.

In addition to the analysis described above, the system 100 may also usesignal strength and models of the cell sector coverage to uniquelyidentify candidate BTSs. As discussed above, a typical BTS has multipletransmitters and multiple antenna elements, each of which is directedfor operation in a sector. In a typical embodiment, a BTS may have threesectors, each of which may be considered a separate BTS. The area ofcoverage of a typical sector may have a pie-shaped area of coverage,such as illustrated in FIGS. 5A–5D. The coverage area of a sector isgenerally determined by measurement at the time a BTS is installed. Thecoverage area is based on factors such as maximum antenna range, maximumtransmitter power, and the like. In some installations, a BTS is dividedinto three sectors with a wide coverage area 170, such as illustrated inFIGS. 5A, 5C and 5D. In other installations, it is desirable to have amore narrow sector, such as a coverage area 172 illustrated in FIG. 5B.

The system 100 can model the coverage area as the pie-shaped coverageareas 170 and 172. However, it is convenient to model the coverage areasas essentially circular distributions. As discussed above, factors suchas antenna backscatter and reflections from man-made objects, terrain,and the like result in a coverage area pattern that may be more circularin shape than pie-shaped. Accordingly, in an exemplary embodiment, thesystem 100 models the coverage area 170 in FIG. 5A as a circularcoverage area 174 while the coverage area 172 in FIG. 5B is modeled as acircular coverage area 176. The coverage areas 170 and 172 arecalculated at the time of installation of the BTS and provide a 99%probability of coverage within that area. The circular coverage areas174, 176, 182 and 184 indicate the area where there is a 99% probabilitythat the mobile unit is within the circle. The center of the coverageareas 174 and 176 are represented by reference numerals 178 and 180,respectively. In an exemplary embodiment, the system 100 uses thecircular model coverage areas 174 and 176, it is possible to calculatethe combined coverage area 160 (see FIG. 4).

As previously discussed, the coverage areas 174 and 176 are used in theprobabilistic calculations for relative phase measurement. The combinedcoverage areas may be linearly combined or weighted based on a scalefactor. The system 100 may calculate scale factors based on receivedsignal strength. One measure of received signal strength is E_(c)/I_(o),which is a measure of the pilot energy accumulated over a 1 PN chipperiod (i.e., E_(c)) to the total power spectral density (i.e., I_(o))in the received bandwidth. Those skilled in the art will recognize thatother power measurements may also be used satisfactorily with the system100. Based on the signal strength, the system 100 assigns a scale factorbased on the strength or weakness of the received signal. The concept ofscale factoring is illustrated in FIGS. 5C and 5D. In FIG. 5C, thereceived signal strength is relatively weak. Thus, the mobile unit maybe located within a relatively wide area with respect to the BTS. Inthis event, the circular coverage area 174 may be expanded by a scalefactor to produce a larger circular coverage area 182, illustrated inFIG. 5C. This wider circular coverage area 182 reflects the fact thatthe mobile unit 10 may be located anywhere within the wider range. Thecenter of the circular coverage area 182 is indicated by the referencenumeral 186.

In contrast, the system 100 may reduce the coverage area if the receivedsignal strength is strong. This indicates that the mobile unit is morelikely close to the BTS rather than farther away. This probability isillustrated in FIG. 5D where a reduced circular area of coverage 184 issmaller in diameter than the circular coverage area 170. The reducedcircular coverage area 184 reflects the fact that there is an increasedprobability that the mobile unit 10 is quite close to the BTS based onthe signal strength. The center of the circular coverage area 184 isindicated by the reference 188.

In an exemplary embodiment, the system may apply a scale factor of 0.9for a strong signal, above a self-preselected threshold, and may apply ascale factor of 1.1 for weak signals (below a predetermined threshold).

As previously discussed, the coverage area calculations are used toestablish the combined coverage area (e.g., the combined coverage area160 of FIG. 4). The cell sector models illustrated in FIGS. 5A–5D mayalso be used to calculate the known area (e.g., the known area 150 ofFIG. 3). In a simple calculation, the coverage area of a single knownBTS may be used as the known area for the coverage area overlap model.Similarly, a single known BTS may be used in combination with a singlecandidate BTS to generate the combined coverage area used in therelative phase model. However, the system 100 can also accommodatecalculations of the known area or combined coverage area that may resultfrom mixing coverage areas from multiple cells. The cells may becombined in a linear fashion or may include weighting, such as the scalefactors applied in FIGS. 5C and 5D or the inverse of the size of eachcoverage area.

The identification process of the system 100 is illustrated in the flowchart of FIG. 6 where, at a start 200, the mobile unit 10 is under powerand a request for location determination has been made. In step 202,system 100 identifies the Reference BTS (e.g., the BTS 12 in FIG. 1). Asnoted above, the Serving BTS is the BTS with which the mobile unit 10initially communicated. In some cases a hand-off may have occurred suchthat the mobile unit 10 is now communicating with a different BTS. Thehand-off process is well known in the art and need not be describedherein. For the sake of the understanding of the present invention, itis sufficient to state that the mobile unit 10 is in communication withthe Reference BTS, which may or may not be the Serving BTS, and hasuniquely identified the Reference BTS.

In step 204, the system 100 generates a candidate list. As previouslydiscussed, signals received from various Measurement BTSs are typicallyidentified only with the respective PN offsets for the Measurement BTSs.Based on the PN offset, a number of candidate BTSs may be identified. Inexampled discussed herein, a PN offset of 25 (i.e., 25×64 chips) wasidentified as a Measurement BTS. In the example described herein, anumber of candidate BTSs throughout the country may have an identical PN25 offset. Each of these candidate BTSs is entered into the candidatelist in step 204.

In step 206, the system 100 narrows the candidate list based on acomparison of coverage areas. As previously discussed, this analysisincludes the elimination of BTSs whose geographic location makes itunlikely that the particular BTS has been detected by the system 100.For example, if the mobile unit 10 has been identified as being locatedsomewhere in the Seattle region based on the communication link 24 withthe Reference BTS 12 (see FIG. 1), it is possible to eliminate BTSs inregions remote from the Seattle area.

As indicated above, the analysis may be performed by the PDE 26 (seeFIG. 1), which may be part of a BTS, remote from the BTS, or may beperformed within the mobile unit 10. The system 100 may initiallyidentify the Reference BTS and, may typically uniquely identify one ormore Measurement BTSs using the processes described above in step 206.Namely, the system 100 may eliminate candidate BTSs that are not in thesame geographic region as the reference BTS. Alternatively, there may bea circumstance in which a particular geographic region has only one BTSwith a particular PN offset. In those circumstances, there is noambiguity as to the unique identity of the candidate BTS. The system 100will identify that candidate BTS as a Measurement BTS.

In step 210 the system 100 uses analytical techniques, such as coveragearea overlap and relative phase difference to further identify candidateBTSs. Furthermore, the system 100 may use signal strength and ananalysis of mixed cell sector positioning to identify the candidateBTSs. In step 210, the system 100 identified the most likely candidatesbased on the analysis in step 208. As discussed above, the most likelycandidate may be selected on the basis of one or more analyticaltechniques. These analyses, such as coverage overlap and relative phasemeasurement may be performed individually or the probabilities may becombined to identify the most likely candidates.

In decision 212, the system 100 determines if all Measurement BTSs havebeen identified. If candidate BTSs remain unidentified, the result ofdecision 212 is NO and the system 100 moves to decision 214. Aspreviously noted, the process of identifying measurement BTSs utilizesknowledge gained from the previous identification of other measurementBTSs in an iterative process. Accordingly, FIG. 6 illustrates aprocessing loop formed by steps 208 and 210 as well as decisions 212 and214. In decision 214, the system 100 determines whether at least one newmeasurement BTS has been identified in this iteration through the loop.Assuming the system 100 is successful in identifying measurement BTSs,the result of decision 214 is YES and the process returns to step 208 toanalyze candidate BTSs with respect to known BTSs, including the atleast one new measurement BTS that was identified on the previous passthrough the loop. The process ends when either all measurement BTSs havebeen identified by the system or when no new BTSs can be identified. Ifall measurement BTSs have been identified, the result of decision 212 isYES and the process ends at 216. If BTSs remain unidentified, but thesystem 100 is unable to identify additional BTSs based on theinformation available, the result decision 214 is NO and the processends at 216.

Using the principles of the present invention, it is possible toidentify all Measurement BTSs detected by the mobile unit 10 (see FIG.1). As those skilled in the art can appreciate, location determinationis more accurate with more Measurement BTSs. If a candidate BTS cannotbe uniquely identified, it is unreliable for AFLT purposes. However,using the techniques of the present invention, it is possible toidentify many of those additional Measurement BTSs and thereby provideadditional sources of measurements that can be used to more reliablydetermine the location of the mobile unit 10.

In the example provided above, the identification process is conductedby the mobile unit 10. However, the identification of candidate BTSs maybe performed by other entities, such as the PDE 26 (see FIG. 1). Forexample, Communication Standard TIA-801 already provides fortransmission of relative phase measurements from the mobile unit to thePDE 26. Additional information, such as precise locations of the BTSs,coverage areas, and the like are also readily determined by any entity,such as the mobile unit 10, a BTS or the PDE. Given this information,any position determining entity may perform the necessary calculationsto uniquely identify each measurement BTS. Accordingly, the presentinvention is not limited to identification of candidate BTSs basedsolely on analysis by the mobile unit 10.

It is to be understood that even though various embodiments andadvantages of the present invention have been set forth in the foregoingdescription, the above disclosure is illustrative only, and changes maybe made in detail, yet remain without the broad principles of theinvention. Therefore, the present invention is to be limited only by theappended claims.

1. In operating a mobile communications unit in a wireless communicationsystem, a method for distinguishing a base station having partialidentification data from another base station having the same partialidentification data, comprising: uniquely identifying a first basestation; receiving transmissions from at least one additional basestation, the transmissions containing only the partial identificationdata; generating a candidate list providing identification of candidatebase stations having the same partial identification data; analyzing thecandidate base stations on the candidate list with respect toidentification data of the first base station; and uniquely identifyinga candidate base station based on the analysis of the candidate basestations.
 2. The method of claim 1 wherein the first base station is aserving base station with which the wireless device has initiallyestablished a communications link.
 3. The method of claim 1 wherein saidgenerating a candidate list providing identification of candidate basestations includes including at least one candidate base station that isout of communication range of said first base station.
 4. The method ofclaim 1 wherein said analyzing the candidate base stations isiteratively performed with respect to other ones of the candidate basestations that have been previously uniquely identified.
 5. The method ofclaim 1 wherein said analyzing the candidate base stations comprisesanalytically determining an area of coverage overlap between a knowncoverage area of the first base station and a coverage area of aselected one of the candidate base stations.
 6. The method of claim 5wherein said determining the area of coverage overlap includesgenerating a probabilistic result and wherein said uniquely identifyingthe candidate base station is based on the probabilistic result.
 7. Themethod of claim 5 wherein said determining the area of coverage overlapfurther comprises altering a coverage area model for a selectedcandidate base station based on a received signal strength of a signalreceived from the selected candidate base station.
 8. The method ofclaim 1 wherein said analyzing the candidate base stations comprisesdetermining a probability that an area of coverage of each of thecandidate base stations overlaps an area of coverage for the first basestation.
 9. The method of claim 8 further comprising deleting a selectedcandidate base station from the candidate list if the selected candidatebase station has a probability of coverage overlap that is less than aprobability of coverage overlap of another candidate base station by apredetermined amount.
 10. The method of claim 9 wherein saidpredetermined amount is greater than 10 times.
 11. The method of claim 1wherein said analyzing the candidate base stations comprisesanalytically determining a relative phase delay between the first basestation and a selected candidate base station.
 12. The method of claim11 wherein said determining the relative phase delay comprisesgenerating a probabilistic result and said uniquely identifying the basestation comprises basing the identity on the probabilistic result. 13.The method of claim 11 further comprising adjusting the relative phasedelay to account for any repeater in the system.
 14. The method of claim11 wherein at least one of the candidate base stations includes arepeater having a known location and signal processing delay, the methodfurther comprising adding the repeater to the candidate list as acandidate base station.
 15. The method of claim 11 wherein saidanalyzing the candidate base stations comprises determining aprobability that a phase delay of each of the candidate base stationsrelative to a phase delay for the first base station corresponds to adistance from each of the candidate base stations to a predeterminedlocation relative to a distance from the first base station to thepredetermined location.
 16. The method of claim 14 wherein thepredetermined location for each of the candidate base stations is anapproximate center of an area of combined coverage of each of therespective candidate base stations and the first base station.
 17. Themethod of claim 16 wherein determining the relative phase delay furthercomprises altering the combined coverage area for a selected basestation based on a received signal strength of a signal received fromthe selected base station.
 18. The method of claim 15 further comprisingdeleting a selected candidate base station from the candidate list ifthe probability of the relative phase delay corresponding to therelative distance for the selected candidate base station is less thanthe probability of the relative phase delay corresponding to therelative distance for other candidate base stations by a predeterminedamount.
 19. The method of claim 18 wherein said predetermined amount isgreater than 10 times.